XGBClassifier - b-cl - default -#

Fitted on a problem type b-cl (see find_suitable_problem), method predict_proba matches output .

XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
          colsample_bynode=1, colsample_bytree=1, enable_categorical=False,
          gamma=0, gpu_id=-1, importance_type=None,
          interaction_constraints='', learning_rate=0.300000012,
          max_delta_step=0, max_depth=6, min_child_weight=1, missing=nan,
          monotone_constraints='()', n_estimators=100, n_jobs=8,
          num_parallel_tree=1, predictor='auto', random_state=0,
          reg_alpha=0, reg_lambda=1, scale_pos_weight=1, subsample=1,
          tree_method='exact', validate_parameters=1, verbosity=None)

index

0

skl_nop

1

onx_size

5005

onx_nnodes

3

onx_ninits

0

onx_doc_string

onx_ir_version

8

onx_domain

ai.onnx

onx_model_version

0

onx_producer_name

skl2onnx

onx_producer_version

1.11.1

onx_ai.onnx.ml

1

onx_

9

onx_op_Cast

1

onx_op_ZipMap

1

onx_size_optim

5005

onx_nnodes_optim

3

onx_ninits_optim

0

fit_classes_.shape

2

fit_n_classes_

2

fit_objective

binary:logistic

fit_estimators_.size

100

fit_node_count

128

fit_ntrees

100

fit_leave_count

114

fit_mode_count

2

%0 X X float((0, 4)) TreeEnsembleClassifier TreeEnsembleClassifier (TreeEnsembleClassifier) class_ids=[0 0 0 0 0 0 0 0 0 0 ... class_nodeids=[1 2 1 2 1 2 1 2 ... class_treeids=[ 0  0  1  1  2  ... class_weights=[-5.38461566e-01 ... classlabels_int64s=[0 1] nodes_falsenodeids=[2 0 0 2 0 0... nodes_featureids=[2 0 0 2 0 0 2... nodes_missing_value_tracks_true=[1 0 0 1 0... nodes_modes=[b'BRANCH_LT' b'LEA... nodes_nodeids=[0 1 2 0 1 2 0 1 ... nodes_treeids=[ 0  0  0  1  1  ... nodes_truenodeids=[1 0 0 1 0 0 ... nodes_values=[2.548984 0.      ... post_transform=b'LOGISTIC' X->TreeEnsembleClassifier output_label output_label int64((0,)) output_probability output_probability [{int64, {'kind': 'tensor', 'elem': 'float', 'shape': }}] label label Cast Cast (Cast) to=7 label->Cast probabilities probabilities ZipMap ZipMap (ZipMap) classlabels_int64s=[0 1] probabilities->ZipMap TreeEnsembleClassifier->label TreeEnsembleClassifier->probabilities Cast->output_label ZipMap->output_probability